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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublikacjaThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Dane BadawczeRaw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.
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Combinatorial Pattern Matching
Konferencje -
Signal Reconstruction from Sparse Measurements Using Compressive Sensing Technique
PublikacjaThe paper presents the possibility of applying a new class ofmathematical methods, known as Compressive Sensing (CS) for recovering thesignal from a small set of measured samples. CS allows the faithful recon-struction of the original signal back from fewer random measurements bymaking use of some non-linear reconstruction techniques. Since of all thesefeatures, CSfinds its applications especially in the areas where, sensing is...
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Marek Kubale prof. dr hab. inż.
OsobyDetails concerning: Qualifications, Experiences, Editorial boards, Ph.D. theses supervised, Books, and Recent articles can be found at http://eti.pg.edu.pl/katedra-algorytmow-i-modelowania-systemow/Marek_KubaleGoogle ScholarSylwetka prof. Marka Kubalego Prof. Marek Kubale pracuje na Wydziale ETI Politechniki Gdańskiej nieprzerwanie od roku 1969. W tym czasie napisał ponad 150 prac naukowych, w tym ponad 40 z listy JCR. Ponadto...
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Hardware accelerated implementation of wavelet transform for machine vision in road traffic monitoring system
PublikacjaW artykule został opisany system monitorowania ruchu drogowego wykorzystujący sprzętową implementację transformacji falkowej. System został zaimplementowany za pomocą procesora zrealizowanego w technologii FPGA i małej kamery z układem konwersji analogowo-cyfrowej. System wykorzystuje transformację falkową do detekcji zatorów na skrzyżowaniach. W artykule zostały przedstawione przykładowe rezultaty rozpoznawania zatorów drogowych...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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3D Machine Vision System for Inspection of Contact Strips in Railway Vehicle Current Collectors
PublikacjaConstruction and technical condition of current collectors is crucial to reliability and safety of railway transportation. According to the Technical Specifications for Interoperability railway vehicles in the European Union should be equipped with carbon contact strips. Excessive wear or defects of contact strips degrade the capability of undisturbed power transmission, cause faster wear of contact wire, and can even result in...
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SSFR Test of Synchronous Machine for Different Saturation Levels using Finite-Element Method
PublikacjaIn this paper the StandStill Frequency Response characteristics (SSFR) of saturated synchronous generator (SG) have been calculated using Finite Element Method (FEM) analysis. In order to validate proposed approach for unsaturated conditions FEM simulation from Flux2D software has been compared with the measurements performed on the 10 kVA, 4- poles synchronous machine ELMOR GCe64a of salient rotor construction, equipped with a...
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublikacjaThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublikacjaThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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DETECTION OF BREATHING AND HEART RATE USING AN ECG SIGNAL MEASURED WHILE BATHING IN THE BATHTUB
PublikacjaNowadays a new area of interest is gaining importance - it is home biomedical examination. Intelligent home can be supported by set of devices for habitants observation. It can be particularly useful for elders or person with some health risks but living alone. One of critical locations within the house is bathroom. One of utilities in the bathroom is a bathtub which is sometimes preferred over shower. There are reports of problems...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublikacjaMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublikacjaPrzedstawiono wyniki badań nagrzewania się podstawowych elementów układu wykonawczego docierarki jednotarczowej o standardowej kinematyce do obróbki powierzchni płaskich. Analizowano przyrost temperatury zespołu napędowego, rolek i pierścieni prowadzących separatory oraz tarczy docierającej i obrabianych elementów. Badano nagrzewanie się układu obróbkowego podczas wyrównywania żeliwnego narzędzia i docierania powierzchni płaskich....
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Techniki szybkiego prototypowania w budowie maszyn = Rapid prototyping techniques in machine building
PublikacjaW artykule omówiono przygotowanie oraz wykonanie poszczególnych elementów maszyn za pomocą techniki szybkiego prototypowania. W pierwszej części przedstawiono technologię wydruku przestrzennego oraz właściwości materiału budulcowego. Druga część artykułu została poświęcona przykładowym wydrukom i ich zastosowaniom w maszynach.
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Sensorless control system of induction machine supplied by voltage source inverter with output filter
PublikacjaThe paper focuses on sensorless control of the induction machines supplied by inverter with the output filters. “The novel” idea of the speed observer which is based on the backstepping approach is shown. The standard structure of the exponential observer is extended by the integrators and additional Z vector. The simulation and experimental results validate the proposed solution.
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublikacjaIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Comparative studies of manufacturing strategies within multi-machine production systems using simulation
PublikacjaZaprezentowano metodykę budowy struktur przestrzennych systemów produkcji typu gniazdowego wg zasad technologii grupowej, wykorzystując zaproponowane modele i algorytmy analizy zbiorów/relacji rozmytych. Generowane, z wykorzystaniem tych algorytmów, przebiegi procesów porównywano z przebiegami procesów w strukturach przestrzennych typu hybrydowego, tj. o wspólnych zasobach. Odnosząc się do zdefiniowanego studium przypadku, wykazano...
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Quality evaluation of computer aided information retrieval from machine typed paper documents
PublikacjaCelem międzynarodowego projektu memorial jest wspomagane komputerowo rozpoznawanie maszynopisów. Referat prezentuje zagadnienie pomiaru jakości takiego procesu. Wskazano w nim potencjalne miejsca pojawiania się błędów oraz przedstawiono i sklasyfikowano odpowiednie miary.
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Optimal selection of the sawdust separation device for a narrow-kerf sawing machine PRW15-M
PublikacjaW pracy przedstawiono granulometryczną analizę rozkładu wiórów i pyłu drzewnego otrzymanego w procesie przecinania suchych pryzm sosnowych na pilarce ramowej wielopiłowej PRW15-M. Wielkości wiórów mieściły się w granicach od 84,7 μm do nawet 14 mm. Te ostatnie są elementami będącymi efektem rozszczepiania dolnej powierzchni pryzmy przez wychodzące z niej ostrza piły. Większośc wiórów z najmniejszych frakcji ma postać sześciennych...
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The Problems of Application of PVD/CVD Thin Hard Coatings for Heavy-Loaded Machine Components
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SIMULATION AND EXPERIMENTAL RESEARCH OF CLAW POLE MACHINE WITH A HYBRID EXCITATION AND LAMINATED ROTOR CORE
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublikacjaIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublikacjaThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublikacjaIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...